Fcγ-receptors Induce Mac-1 (CD11b/CD18) Mobilization and Accumulation in the Phagocytic Cup for Optimal Phagocytosis
Bibliographic record
Abstract
Functional interactions between Fcgamma-receptors (FcgammaR) and the beta2 integrin Mac-1 (CD11b/CD18) have been described, but the molecular basis of this relationship remains unclear. Although the glycosylphosphatidylinositol-linked receptor FcgammaRIIIB of human neutrophils is constitutively associated with Mac-1, we found no evidence for direct physical association between Mac-1 and the FcgammaR of mouse macrophages, which are transmembrane proteins. Nevertheless, Mac-1 accumulated in the phagocytic cup following engagement of FcgammaR by IgG-opsonized particles. Blocking the CD18 chains of beta2 integrins by using specific antibodies reduced Mac-1 accumulation in the cup. These antibodies or the addition of the recombinant CD11b I-domain inhibited the ingestion of IgG-opsonized particles. FcgammaR cross-linking stimulated cell adhesion to surfaces coated with Mac-1 ligands and in addition enabled macrophages to bind C3bi-opsonized particles, indicating that FcgammaR-derived signals induce activation of Mac-1. Measurements of fluorescence recovery after photobleaching revealed that whereas most (>80%) of Mac-1 is immobile in resting cells, stimulation of FcgammaR markedly increases the mobile fraction of the integrin. Activation of Mac-1 by FcgammaR required the activity of Src family tyrosine kinases, phosphatidylinositol 3-kinase and phospholipase C, with the release of diacylglycerol and stimulation of protein kinase C. Because elevated cytosolic Ca2+ was not required, we suggest that novel protein kinase C isoforms are involved in Mac-1 activation. These results suggest that FcgammaR stimulation promotes Mac-1 clustering into high avidity complexes in phagocytic cups by releasing the integrin from cytoskeletal constraints and enhancing its lateral diffusion. FcgammaR can enhance host defense by activating Mac-1 (and possibly other integrins), having a synergistic effect on pathogen engulfment and promoting the adherence of phagocytes at sites of infection.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".